单片机与嵌入式系统应用最新文献_第3页

Enhancement of Range-Based $3mathrm{D}$ Positioning via Angle of Arrival Information 基于到达角度信息的基于距离的$3 mathm {D}$定位增强

单片机与嵌入式系统应用 Pub Date : 2018-05-01 DOI: 10.1109/ICESIT-ICICTES.2018.8442056

Chatchanan Varojpipath, Peerawit Chaichanamongkol, Pornkitti Mahitthiburin, Prapun Suksompong, C. Charoenlarpnopparut

引用次数: 0

Stock Price Prediction With Long Short-Term Memory Recurrent Neural Network 基于长短期记忆递归神经网络的股票价格预测

单片机与嵌入式系统应用 Pub Date : 2018-05-01 DOI: 10.1109/ICESIT-ICICTES.2018.8442069

C. Jeenanunta, Rujira Chaysiri, L. Thong

{"title":"Stock Price Prediction With Long Short-Term Memory Recurrent Neural Network","authors":"C. Jeenanunta, Rujira Chaysiri, L. Thong","doi":"10.1109/ICESIT-ICICTES.2018.8442069","DOIUrl":"https://doi.org/10.1109/ICESIT-ICICTES.2018.8442069","url":null,"abstract":"In this paper, we investigate the prediction of daily stock prices of the top five companies in the Thai SET50 index. A Recurrent Neural Network (RNN) with Long Short-Term Memory (LSTM) is applied to forecast the next daily stock price (High, Low, Open, Close). Deep Belief Network (DBN) is applied to compare the result with LSTM. The test data are CPALL, SCB, SCC, KBANK, and PTT from the SET50 index. The purpose of selecting these five stocks is to compare how the model performs in different stocks with various volatility. There are two experiments of five stocks from the SET50 index. The first experiment compared the MAPE with different length of training data. The experiment is conducted by using training data for one, three, and five-year. PTT and SCC stock give the lowest median value of MAPE error for five-year training data. KBANK, SCB, and CPALL stock give the lowest median value of MAPE error for one-year training data. In the second experiment, the number of looks back and input are varied. The result with one look back and four inputs gives the best performance for stock price prediction. By comparing different technique, the result show that LSTM give the best performance with CPALL, SCB, and KTB with less than 2% error. DBN give the best performance with PTT and SCC with less than 2% error.","PeriodicalId":57136,"journal":{"name":"单片机与嵌入式系统应用","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86818105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 11

Message Passing-Vector Symbol Decoding for LDPC Codes with Nonbinary Symbols 非二进制LDPC码的消息传递-矢量符号解码

单片机与嵌入式系统应用 Pub Date : 2018-05-01 DOI: 10.1109/ICESIT-ICICTES.2018.8442073

U. Tuntoolavest, Chayanon Athanan, Koravit Panwong

引用次数: 4

Appropriate Features to Determine Correlation in EMG Signals and Biting Force in Occlusion System 确定咬合系统中肌电信号与咬合力相关性的适当特征

单片机与嵌入式系统应用 Pub Date : 2018-05-01 DOI: 10.1109/ICESIT-ICICTES.2018.8442067

S. Poomsombut, C. Limsakul, P. Phukpattaranont

引用次数: 1

Speed Control Under Load Uncertainty of Induction Motor Using Neural Network Auto-Tuning PID Controller 基于神经网络自整定PID控制器的异步电机负载不确定性转速控制

单片机与嵌入式系统应用 Pub Date : 2018-05-01 DOI: 10.1109/ICESIT-ICICTES.2018.8442062

Wasu Wasusatein, Sukhumpat Nittayawan, W. Kongprawechnon

{"title":"Speed Control Under Load Uncertainty of Induction Motor Using Neural Network Auto-Tuning PID Controller","authors":"Wasu Wasusatein, Sukhumpat Nittayawan, W. Kongprawechnon","doi":"10.1109/ICESIT-ICICTES.2018.8442062","DOIUrl":"https://doi.org/10.1109/ICESIT-ICICTES.2018.8442062","url":null,"abstract":"Induction motor has been an important machine in many applications especially in Electric Vehicles(EVs), The improve in performance of the induction motor will result in a more stable and efficient drive system of the EV which will be beneficial for future applications which was achieved through the introduction of Variable-Speed Drive system. However, in this non ideal world, uncertainty must be considered. Load of induction motor has high uncertainty which cause a high degree of instability or degradation in performance of the system. In order to keep induction motor in control to uncertainty of load, a suitable controller should be introduced to solve the problem. Neural Network Controllers are used widely in non-linear system due to its adaptivity to new conditions as the controller uses a learning system from past inputs and outputs. This study is to apply neural network in auto-tuning PID controller for improving the accuracy of induction motor drive in electrical vehicles when load is uncertain. The final objective is to improve, through the addition of neural network, the robustness and performance of the induction motor.","PeriodicalId":57136,"journal":{"name":"单片机与嵌入式系统应用","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81033241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

PDLC film's energy consumption and performance for light filtration system 光过滤系统用PDLC薄膜的能耗与性能

单片机与嵌入式系统应用 Pub Date : 2018-05-01 DOI: 10.1109/ICESIT-ICICTES.2018.8442057

Wiwat Keyoonwong, W. Khan-ngern, Paritpong Tavichaiyut Viritpol Ruxsri, Vishnu Raksasataya

引用次数: 1

Missing Value Estimation of Energy Consumption of Multi-Unit Air Conditioners using Artificial Neural Networks 基于人工神经网络的多机组空调能耗缺失值估计

单片机与嵌入式系统应用 Pub Date : 2018-05-01 DOI: 10.1109/ICESIT-ICICTES.2018.8442059

Paradorn Pimporn, S. Kittipiyakul, J. Kudtongngam, H. Fujita

引用次数: 2

Hidden Dot Patterns Recognition using CNNs on Raspberry Pi Zero W 在树莓派零W上使用cnn的隐藏点模式识别

单片机与嵌入式系统应用 Pub Date : 2018-05-01 DOI: 10.1109/ICESIT-ICICTES.2018.8442050

K. Sukvichai, Pearpeerune Uthaisang, Patchareeporn Chuengsutthiwong, Pruttapon Maolanon

{"title":"Hidden Dot Patterns Recognition using CNNs on Raspberry Pi Zero W","authors":"K. Sukvichai, Pearpeerune Uthaisang, Patchareeporn Chuengsutthiwong, Pruttapon Maolanon","doi":"10.1109/ICESIT-ICICTES.2018.8442050","DOIUrl":"https://doi.org/10.1109/ICESIT-ICICTES.2018.8442050","url":null,"abstract":"A talking pen is the evolutional way of learning especially for children because it is fun and interactive. Commercial talking pen use a small infrared camera to capture the hidden dot patterns that hidden around a book's page. Specific sounds are generated according to the location of the pen on the pages. This image processing for recognition technique is complex and need calculation power because it had to calculate relative location and orientation of dots in a group. Although, the talking pen is successful product but it is not flexible to add new pattern or uses different set of patterns. In this research, the new approach for hidden dot pattern recognition is proposed. Convolutional neural networks or CNNs is selected as the recognition software. The system is built on Raspberry Pi Zero W hardware with Raspbian operating system and TensorFlow platform. MobileNet is used in the research since it small and effective for limited resources platform. MobileNet is trained by using the infrared images that captured by infrared camera module that connected to Raspberry Pi. Result shows that the accuracy of the proposed method is good enough and the response is fast enough to be implemented into the real-time commercial product and has ability to expand to any other kind of patterns without limit because the learned network can be updated easily without alter recognition software.","PeriodicalId":57136,"journal":{"name":"单片机与嵌入式系统应用","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78611699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

CF Planter: A Toolset for Semi-automatic Thai Treebank Construction CF Planter:一个半自动泰国树库构建工具集

单片机与嵌入式系统应用 Pub Date : 2018-05-01 DOI: 10.1109/ICESIT-ICICTES.2018.8442061

Pechlada Seenual, Thodsaporn Chay-intr, T. Theeramunkong

{"title":"CF Planter: A Toolset for Semi-automatic Thai Treebank Construction","authors":"Pechlada Seenual, Thodsaporn Chay-intr, T. Theeramunkong","doi":"10.1109/ICESIT-ICICTES.2018.8442061","DOIUrl":"https://doi.org/10.1109/ICESIT-ICICTES.2018.8442061","url":null,"abstract":"To fasten treebank construction, it is necessary to design an integrated annotation tool that includes word segmenter, sentence parser for initial tree suggestion, tree visualizer, tree-structure editor, and collaborative functions. In the past, existing tools did not consider an integrated platform that provides preprocessing, automated or semi-automated mechanism for parse tree suggestion, as well as tagged corpus data management. This paper presents a so-called CF Planter, a toolset for semi-automatic Thai treebank construction that consist of word segmenter, part-of-speech tagger, statistical parser, a web-based GUI for syntactic tree refinement and management. Given an input sentence, its most likely syntactic tree is automatically suggested and visualized to an annotator for manual correction before adding into the treebank repository. Whenever a new syntactic tree is appended into the treebank, the treebank repository is iteratively refined by computing a set of newly revised grammar rules based on revised probabilities. Toolset is performed to severally illustrate with grammar frequencies. The toolset facilitates annotators to easily tag tree structure for an input sentence. Finally, the process of automatic suggestion of syntactic tree is evaluated.","PeriodicalId":57136,"journal":{"name":"单片机与嵌入式系统应用","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82483546","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Design and Implementation of Real-time Embedded Data Acquisition and Classification with Web-based Configuration and Visualization 基于web配置和可视化的实时嵌入式数据采集与分类的设计与实现

单片机与嵌入式系统应用 Pub Date : 2018-05-01 DOI: 10.1109/ICESIT-ICICTES.2018.8442071

S. Nuratch

{"title":"Design and Implementation of Real-time Embedded Data Acquisition and Classification with Web-based Configuration and Visualization","authors":"S. Nuratch","doi":"10.1109/ICESIT-ICICTES.2018.8442071","DOIUrl":"https://doi.org/10.1109/ICESIT-ICICTES.2018.8442071","url":null,"abstract":"This research proposes some useful and practical techniques to design and implement the real-time embedded data acquisition and classification. A web-based used as graphical user interface is also provided to visualize data, parameters and behaviors of the proposed system. A low-cost microcontroller is chosen to run special bootloader and application program. The application program is designed and implemented using non-blocking event-driven realtime operating system. It reads data from sensors, performs K-means classification algorithm, and sends data and system states to the web-based application running on a web browser. In addition, the microcontroller system is designed to support many IoT applications. It is composed of all basic inputs and outputs, e.g., ADCs, PWMs, Wi-Fi, USB-to-UART and data storage. The users can visualize the measured data and examine behaviors of the K-means algorithm on the web browser in real-time. The web-based application is designed and implanted using new technology of web-based application development techniques. It can be run on any device that has web browser. The microcontroller and web-based application can exchange their data over internet network using HTTP, MQTT or WebSockets protocol. It supports serial port communication as well. The experimental results show that the proposed system and algorithms running on the microcontroller and web browser can perform data acquisition and classification in real-time manner and it can be used in real-world applications as expected.","PeriodicalId":57136,"journal":{"name":"单片机与嵌入式系统应用","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81335466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3